Data Mapping System for Investment Recommendations
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Solution Overview
Problem
Individuals face information overload when trying to make investment decisions, as they are overwhelmed by numerous stocks and related metrics, making it difficult to identify desirable investments.
Innovation Solution
A data mapping method that processes online banking transaction data to associate it with company identifiers such as stock tickers, allowing for a customized graphical user interface to prompt users about investment opportunities based on their transaction history, using fuzzy string matching and supervised machine learning for improved recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If individuals are provided with comprehensive investment information including numerous stocks and metrics, then the completeness of information is improved, but the ease of decision-making deteriorates due to information overload
Solution Approach 1:
The patent extracts only the most relevant investment information from the vast available data by analyzing user spending patterns and identifying corresponding companies. Instead of presenting all available stock information, the system selectively extracts and presents only those investment opportunities that align with the user's demonstrated interests based on their transaction history, thereby reducing information overload while maintaining decision-relevant completeness
Solution Approach 2:
The patent applies local quality by customizing the information presentation according to each user's specific spending patterns and preferences. Rather than providing uniform comprehensive information to all users, the system tailors the investment recommendations to match individual user profiles, presenting different subsets of information to different users based on their local (individual) characteristics and needs
2Ease of operation
If a customized graphical user interface is implemented to filter and present relevant investment opportunities, then the ease of decision-making is improved, but the device complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing user spending patterns and generating personalized investment recommendations without requiring manual user configuration or complex interaction. The data mapping process autonomously connects transaction categories to company identifiers and generates filtered investment lists, reducing the need for complex user-side processing while maintaining customized presentation
Solution Approach 2:
The patent introduces an intermediary data mapping layer that translates between transaction data and investment recommendations. This intermediary component handles the complex data processing and filtering tasks, acting as a mediator between the raw transaction data and the simplified user interface, thereby isolating the complexity from the user-facing system
Data Source
AI summary
Methods, systems, and techniques for data mapping. Company identifiers and an electronic commerce transaction history, such as an online banking transaction history, of a user are retrieved from one or more data repositories. The electronic commerce transaction history includes purchases made from one or more companies identified by the company identifiers. Data mapping is then performed to associate the company identifiers with the purchases represented in the electronic commerce transaction history to identify the companies represented by the company identifiers from which the user made purchases. The company identifiers are then caused to be displayed on a graphical user interface as suggestions to the user as investment suggestions.